Senior Data Engineer

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Chapter247 Infotech

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Job Summary


Job Type
-

Seniority
Senior

Years of Experience
Information not provided

Tech Stacks
Python SQL Spark Azure UNIX Databricks pySpark Analytics Snowflake ETL

Job Description

Responsibilities:

  • Design, develop, and implement data warehousing solutions with a strong focus on Snowflake, Databricks, and Azure.
  • Build productized data ingestion and processing pipelines to facilitate seamless data integration.
  • Architect, design, and operationalize large-scale data and analytics solutions on Snowflake Cloud Data Warehouse.
  • Develop and maintain ETL pipelines for data ingestion and transformation using Python and SnowSQL.
  • Create scripts using Unix, Python, etc., for Extract, Load, and Transform (ELT) processes.
  • Provide production support for data warehouse issues, including data load, transformation, and translation problems.
  • Translate business requirements for BI and reporting into database design and reporting solutions.
  • Understand data transformation and translation requirements and leverage appropriate tools.
  • Develop, automate, and document data pipelines using modern cloud-based technologies.
  • Optimize Snowflake accounts by managing compute and storage, ensuring performance, and handling administrative tasks.
  • Utilize Snowflake utilities such as SnowSQL, SnowPipe, and Time Travel, and write stored procedures and manage tasks within Snowflake.
  • Engineer platform components like data pipelines, data masking, data orchestration, data quality, data governance, and analytics in Snowflake.
  • Implement Snowflake best practices for managing load operations and optimizing performance.
  • Design and develop secure data access using Role-Based Access Control (RBAC), secure views, and dynamic data masking.
  • Utilize data replication for secure data sharing across accounts and managing failover scenarios.
  • Apply advanced performance tuning methodologies in Snowflake to enhance query performance and reduce processing time.


Qualifications:

  • Minimum of 3+ years of experience working in Snowflake, ADF and Data Bricks.
  • Minimum of 4+ years of experience in implementing data warehousing solutions.
  • Strong experience in building data ingestion and processing pipelines.
  • Solid understanding of large-scale data and analytics solution architecture on Snowflake Cloud Data Warehouse.
  • Proficiency in developing ETL pipelines using Python and SnowSQL.
  • Hands-on experience with Unix, Python, and other scripting languages for ELT processes.
  • Experience in providing production support for data warehouse issues.
  • Ability to translate BI and reporting requirements into database design.
  • In-depth knowledge of data transformation, translation requirements, and appropriate tools.
  • Familiarity with cloud-based data pipeline automation and documentation.
  • Demonstrated understanding of Snowflake architecture, including compute and storage management.
  • Proficiency with Snowflake utilities and stored procedures.
  • Expertise in data pipeline engineering, data masking, data orchestration, data quality, data governance, and analytics in Snowflake.
  • Experience with Snowflake best practices, load operation management, and performance optimization.
  • Knowledge of data governance in Snowflake, secure views, dynamic data masking, and RBAC.
  • Experience with data replication for secure data sharing and failover management.
  • Strong scripting skills in Spark, PySpark, Snowpark, or SQL are highly desirable.
  • SnowPro certification is a plus.



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